A free energy principle for the brain

@article{Friston2006AFE,
  title={A free energy principle for the brain},
  author={Karl J. Friston and James M Kilner and Lee M. Harrison},
  journal={Journal of Physiology-Paris},
  year={2006},
  volume={100},
  pages={70-87}
}

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References

SHOWING 1-10 OF 62 REFERENCES
A theory of cortical responses
  • Karl J. Friston
  • Biology, Psychology
    Philosophical Transactions of the Royal Society B: Biological Sciences
  • 2005
TLDR
The aims of this article are to encompass many apparently unrelated anatomical, physiological and psychophysical attributes of the brain within a single theoretical perspective and to provide a principled way to understand many aspects of cortical organization and responses.
Learning and inference in the brain
Dynamic representations and generative models of brain function
The Helmholtz Machine
TLDR
A way of finessing this combinatorial explosion by maximizing an easily computed lower bound on the probability of the observations is described, viewed as a form of hierarchical self-supervised learning that may relate to the function of bottom-up and top-down cortical processing pathways.
Bayesian integration in sensorimotor learning
TLDR
This work shows that subjects internally represent both the statistical distribution of the task and their sensory uncertainty, combining them in a manner consistent with a performance-optimizing bayesian process.
Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects.
TLDR
Results suggest that rather than being exclusively feedforward phenomena, nonclassical surround effects in the visual cortex may also result from cortico-cortical feedback as a consequence of the visual system using an efficient hierarchical strategy for encoding natural images.
On the computational architecture of the neocortex. II. The role of cortico-cortical loops.
TLDR
A hypothesis on the role of the reciprocal, topographic pathways between two cortical areas, one often a 'higher' area dealing with more abstract information about the world, the other 'lower', deals with more concrete data, is put forward.
Uncertainty, Neuromodulation, and Attention
On the computational architecture of the neocortex
  • D. Mumford
  • Computer Science
    Biological Cybernetics
  • 2004
TLDR
A hypothesis on the role of the reciprocal, topographic pathways between two cortical areas, one often a ‘higher’ area dealing with more abstract information about the world, the other ‘lower’, deals with more concrete data is put forward.
...
...